SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
An evaluation of phrasal and clustered representations on a text categorization task
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
User-defined relevance criteria: an exploratory study
Journal of the American Society for Information Science - Special issue: relevance research
Learning and Revising User Profiles: The Identification ofInteresting Web Sites
Machine Learning - Special issue on multistrategy learning
Users' criteria for relevance evaluation: a cross-situational comparison
Information Processing and Management: an International Journal
Term Weighting in Information Retrieval Using the Term Precision Model
Journal of the ACM (JACM)
Learning to construct knowledge bases from the World Wide Web
Artificial Intelligence - Special issue on Intelligent internet systems
Machine Learning
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Enabling Concept-Based Relevance Feedback for Information Retrieval on the WWW
IEEE Transactions on Knowledge and Data Engineering
SIFT: a tool for wide-area information dissemination
TCON'95 Proceedings of the USENIX 1995 Technical Conference Proceedings
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Current Web search engines are not able to adapt their operations to the evolving needs, interests and preferences of the users. To cope with this problem we developed a system able to classify HTML (or, XML) documents into user pre-specified categories of interests. The system processes the user profile and a set of representative documents- for each category of interest, and produces a classification schema- presented as a set of representative category vectors. The classification schema is then utilized in order to classify new incoming Web documents to one (or, more) of the pre-specified categories of interest. The system offers the users the ability to modify and enrich his/her profile depending on his/her current search needs and interests. In this respect the adaptive and personalized delivery of Web-based information is achieved. Experimental results on an indicative collection of Web-pages show the reliability and effectiveness of our approach.